The Influence of Selective Attention on Auditory Localization in Younger and Older Adults

Transcription

1 The Influence of Selective Attention on Auditory Localization in Younger and Older Adults by Stephanie Yung A thesis submitted in conformity with the requirements for the degree of Master of Arts Department of Psychology University of Toronto Copyright by Stephanie Yung 2016

2 The Influence of Selective Attention on Auditory Localization in Younger and Older Adults Abstract Stephanie Yung Master of Arts Department of Psychology University of Toronto 2016 Auditory localization, the ability to locate sounds, declines with age due to changes in peripheral and central auditory processing. As selective attention is typically preserved in older adults, drawing their attention towards the stimulus before it occurs may improve auditory localization. This study evaluated this hypothesis by precueing younger and older participants towards a likely location of the upcoming target (a broadband noise) with a visual attentional cue. The attentional cues either provided a) correct information about the upcoming target location (valid) b) incorrect information about the upcoming target location (invalid), or c) no information about the upcoming target location (neutral). Participants estimated the target s location on a schematic drawing of the testing environment. Akin to younger adults, older adults made less errors and biases, and faster responses with valid cues. This suggests that older adults can employ selective attention to improve auditory localization, similar to younger adults. ii

3 Acknowledgments I would like to thank my supervisors Dr. Jennifer Campos and Dr. Ian Spence for their patience, guidance, and sharing their expertise with me. I would also like to thank Bruce Haycock for programming the auditory localization task. Last but not least, I would like to thank my external examination committee member, Dr. Claude Alain, for his generosity of time. iii

4 Table of Content Acknowledgments... iii Table of Content... iv 1 Introduction Overview Mechanisms of Auditory Localization Age Differences in Auditory Localization Selective Attention and Auditory Localization Rationale and Hypotheses Method Participants Materials Audiometric Testing Auditory Target Testing Environment Visual Cues and Response Auditory Localization Task Procedure Design Results Absolute Error Signed Error Response Time Discussion Localization Accuracy Response Time Summary of the Results Conclusion References iv

5 List of Figures Figure 1. Diagram of the testing environment in aerial view. Participants sat at equidistance (2.14 m) from the five physical loudspeakers at -90, -28, 0, +28, +90. The loudspeakers were hidden from view by a 240 projection screen. Figure 2. Trial procedure of the auditory localization task (A). This exemplifies a valid trial in the auditory localization task. The attentional cue was centered at -90. The red circle indicates that the target was presented at -90. Note that participants were not shown the placements of the physical loudspeakers. (B) is a screenshot of the auditory localization task during feedback. Figure 3. Mean absolute error (degrees) between the three different attentional cue types collapsed across location and age groups. Error bars represent ±2 SE. Figure 4. Mean absolute error (degrees) between the five locations collapsed across age groups and the attentional cue types. Error bars represent ±2 SE. Figure 5. Mean absolute error (degrees) between the five locations clustered by the three different attentional cue types. Error bars represent ±2 SE. Figure 6. Mean signed error (degrees) between the three different attentional cue types collapsed across location and age groups. Error bars represent ±2 SE. Figure 7. Mean signed error (degrees) between the five locations collapsed across age groups and the attentional cue types. The error bars represent ±2 SE. Figure 8. Mean signed error (degrees) between the five locations clustered by the three different attentional cue types. Error bars represent ±2 SE. Figure 9. Mean response time (ms) between the three different attentional cue types collapsed across location and age groups. Error bars represent ±2 SE. Figure 10. Mean response time (ms) between the five locations collapsed across age groups and the attentional cue types. Error bars represent ±2 SE. Figure 11. Mean response time (ms) between the three different attentional cue types clustered by age groups. Error bars represent ±2 SE. Figure 12. Mean response time (ms) between the five locations clustered by age groups. Error bars represent ±2 SE. v

6 1 Introduction 1.1 Overview Hearing helps humans become spatially aware of their environment. If one hears tires screeching from behind, one can assume that there is a car behind them. Locating a bird may also be easier by listening to its call, similar to following a familiar voice to find a friend in the crowd. In the literature, this ability to locate objects through hearing is termed auditory localization (Briley & Summerfield, 2014; Freigang et al., 2015; Moore, 2013). Despite its importance in everyday life, auditory localization declines with age (Freigang et al., 2015). Even the healthiest older adults with no or mild hearing loss are not as accurate as younger adults in localizing sounds (e.g., Freigang et al., 2014). This suggests that the age differences in auditory localization may be due to changes in the central auditory system (the interactions between the ears and the brain) rather than the peripheral auditory system (ear structures; Freigang et al., 2015). One way to compensate for the declines in auditory localization may be to use selective attention, a higher-order cognitive ability that has been found to be preserved with age (e.g., Groth & Allen., 2000; Guerreiro et al., 2014). Selective attention is the ability to attend to relevant information while ignoring irrelevant information, and this can be used when there is directional knowledge about the upcoming stimulus (Posner, 1980). While studies have showed that selective attention can improve auditory localization in younger adults (e.g., Golob & Holmes, 2011), it is still unclear whether it has the same influence on older adults. Therefore, this study aimed to understand the interaction between auditory localization and attention as we age. Of particular interest was whether older adults can locate a broadband noise target presented in the horizontal plane (left, right, and directly in front of the listener s head) as quickly and as accurately as younger adults when attention is directed towards its upcoming location. Thus, three different types of visual attentional cues provided the target s upcoming location: 1) valid cues, which correctly indicated the upcoming target location; 2) invalid cues, which incorrectly indicated the upcoming target location; and 3) neutral cues, which provided no directional information about the upcoming target location. Based on the current literature (Groth & Allen, 2000; Golob et al., 2002; Golob & Holmes, 2011), correct information about the 1

7 upcoming target location should improve older adults accuracy and response time to a greater extent than younger adults (described further below). To begin, I will first review the mechanisms of auditory localization. Then, I will review the current literature on the age differences in auditory localization and the influence of selective attention on auditory localization with younger adults. Based on the reviewed literature, the hypotheses and the study design will be described. Finally, the results and its interpretations will be discussed. 1.2 Mechanisms of Auditory Localization Two sound cues are used to locate sounds in the horizontal plane (e.g., left, right and directly in front of the listener s head): the interaural time difference (ITD) and the interaural level difference (ILD). The temporal difference in the arrival of the sound to each ear is termed the interaural time difference (Middlebrooks & Green, 1994). For instance, when a sound arrives at the right ear first, its perceived location should be closer to the right side of the listener s head. The difference of the sound intensity in each ear is termed the interaural level difference. For instance, when a sound is louder at the right ear, its perceived location should be closer to the right side of the listener s head (Akeroyd, 2006, 2014; Grothe et al., 2010; Middlebrooks & Green, 1994; Moore, 2013). Auditory localization thus involves the detection of the sound cues in the peripheral auditory system (the structure of the ears), and then the integration of the sound cues in the central auditory system (the interaction between the ears and the brain; Middlebrooks & Green, 1994). Interestingly, not all sounds produce reliable ITDs and ILDs for localization. Broadband and everyday noise, such as speech or bird chirps, rely on the comparisons between ITDs and ILDs in each ear (Akeroyd, 2006, 2014). However, pure-tone noise, such as high- and low-frequency noise, produce either ILDs or ITDs, respectively (Middlebrooks & Green; 1991; Moore, 2013). Therefore, broadband and everyday noise are localized with higher accuracy because they produce ITDs and ILDs, whereas high- and low-frequency noise are harder to localize because they have one or the other (e.g., Abel et al., 2000; Freigang et al., 2015; Middlebrooks & Green; 1991; Moore, 2013; see also Rayleigh, 1907). 2

8 Different environments can also affect the sound cues and subsequent auditory localization (e.g., Kopčo et al., 2007). Most everyday environments are reverberant, which means there are surfaces that reflect sound waves (e.g., classrooms, concert halls, caves). Environments that absorb or weaken sound reflections are anechoic (e.g., sound booth). Broadband noise stimuli have been found to be localized with high accuracy in semi-reverberant and anechoic environments (Abel et al., 2000; Dobreva et al., 2011; Kopčo et al., 2007); however, pure-tone noise stimuli are localized most accurately in environments with anechoic properties (Ahveninen et al., 2014; Brungart et al., 2011; Freigang et al., 2014). Freigang et al. (2015) explained that pure-tone noise may be hard to localize in non-anechoic environments because they have fewer sound cues, thus the integrity of the pure-tone noise may be more modulated by acoustical properties such as reverberation. For instance, Abel et al. (2000) found that high-frequency noise was harder to localize in a semi-reverberant environment because the reflective surfaces may have increased the sound intensity differences between each ear (ILDs). In other words, listeners perceived the high-frequency noise as farther away from its actual location because the sound reflections may have made the sound waves in each ear louder than they actually were. Few studies have examined auditory localization in fully reverberant environments (Ahveninen et al., 2014; Kopčo et al., 2007). Understandably, these environments may introduce uncontrollable factors as discussed above (see also Zahorik et al., 2005, for how reverberation may bias distance perception). However, most sounds in everyday life are heard in reverberant environments. Thus, the localization of pure-tone noise in simple environments such as anechoic or semi-reverberant environments may not be as generalizable to real-life settings. To improve our knowledge of auditory localization in realistic settings, this study aimed to extend the current literature by using a broadband noise in a typically, reverberant indoor setting. 1.3 Age Differences in Auditory Localization Most studies on auditory localization have focused on younger adults (e.g., Ahveninen et al., 2014; Akeroyd, 2006; Arnott & Alain, 2002; Brungart et al., 2011; Golob & Holmes, 2011; Middlebrooks & Green, 1991; Savel, 2009; Stevens & Newman, 1936; Tiippana et al., 2011; Wood & Bizley, 2015), but when older adults are compared to younger adults, older adults localized sounds less accurately (Abel et al., 2000; Dobreva et al., 2011; Freigang et al., 2014). For instance, Abel et al. (2000) asked younger and older adults to localize broadband noise and 3

9 high- and low-frequency noise from different arrays of speakers positioned in the horizontal plane. Listeners localized the sounds by pressing buttons that corresponded with each speaker. Ultimately, they found that the localization estimates of the sounds presented from the lateral positions were less accurate in older adults than in younger adults. Further, overall localization accuracy was higher by 15% in younger listeners compared to older listeners. This was also found by Freigang et al. (2014) who presented high- and low-frequency noises positioned in the horizontal plane; sounds presented more laterally were more difficult to localize than sounds presented towards the center, and the overall accuracy of the younger listeners was 21% higher than older listeners. The mechanisms that account for the age differences in auditory localization have not been elucidated. Dobreva et al. (2011) noted that it is especially difficult to disentangle the central and peripheral auditory changes that may contribute to problems with auditory localization in healthy older adults. For instance, even the healthiest older adult may have slight hearing difficulty (especially in the higher frequencies) due to functional changes in the peripheral auditory system. However, Abel et al. (2000) and Freigang et al. (2014) did not find strong evidence that higher hearing thresholds, as measured by audiometric tests, were associated with poorer localization accuracy. On the other hand, Freigang et al. (2015) reviewed that Freigang et al. s 2014 study may not have found strong associations between hearing thresholds and auditory localization performances because they tested older adults under 65 years of age. According to Freigang et al. (2015), the biggest changes in peripheral hearing manifest after 65 years. Nevertheless, Freigang et al. (2015) reviewed that the age-related changes in the central auditory system may better explain localization problems in healthy older adults. Specifically, functional changes (e.g., loss of hair cells in the cochlea) can lead to temporal jitter in afferent neuronal signal processing, and subsequently reduce the transmission of precise temporal information of the sound cues (p. 361; see also Pichora-Fuller & Schneider, 1998). This suggests that older adults may locate sounds less accurately because the integration of the sound cues from each ear is delayed. As Dobreva et al. (2011) mentioned, the interaction between peripheral auditory processing and central auditory processing are indeed difficult to disentangle. Due to structural declines in the 4

10 peripheral auditory system, the temporal processing of the central auditory system suffers (Freigang et al., 2015). However, one way to control for some of the effects associated with peripheral deficits is to test older adults with pure-tone hearing thresholds that are comparable to younger adults under ideal conditions (i.e. in a sound booth). Therefore, the current study recruited older adults who are at least 65 years of age with normal hearing (as defined by <30 db for frequencies from 0.25, 0.50, 0.75, 1, 2, 3, and 4kHz; International Organization for Standardization (ISO), 2000). 1.4 Selective Attention and Auditory Localization Selective attention may compensate for the age-related changes in the peripheral and central auditory systems. Selective attention is the cognitive ability to attend to relevant information while ignoring irrelevant information (Groth & Allen, 2000). There are numerous theories on how attention is deployed, but most posit that there are attentional processing resources that are differentially distributed based on the task demands (Feng & Spence, 2013). For example, in Eriksen and St. James s zoom lens analogy (1986), if the size of the attended field is large, the processing resources within this field will be distributed more sparsely. While this ensures the target(s) will be detected, accuracy and/or response time to the target(s) may be impaired. On the other hand, if the size of the attended field is smaller, the processing resources will become focused on a denser area; thus, the responses to the target(s) within this field may be more accurate and/or faster. The zoom lens analogy has been traditionally applied to visual information (e.g., Madden et al., 1994; Madden, 2007), demonstrating that older adults respond to visual targets more slowly and less accurately when they attend to a larger field than a smaller field. However, when older adults have prior knowledge about the upcoming target location, they respond faster and more accurately. Thus, prior knowledge about the target may decrease the size of the attended field and ensure the processing resources are organized to respond to the targets faster and more accurately. In the context of auditory localization tasks, younger adults seem to benefit from employing selective attention (e.g., Golob & Holmes, 2011). In a series of auditory localization experiments, Rhodes (1987) informed younger adults that an upcoming sound would have a high chance of 5

11 appearing in the same location as it did during the previous trial (but not always). Therefore, the previous trial location precued the likely location of the upcoming trial. Rhodes (1987) found that the responses of the precued locations were faster and more accurate than non-cued locations. Since then, more studies have demonstrated the benefit of precueing in improving auditory localization in various planes in younger adults and in those with visual impairments (e.g., Collins & Schirillo, 2013; Bausenhart et al., 2007; Föcker et al., 2010; Golob & Holmes, 2011; Hiscock et al., 1999; Lee & Spence, 2015; Teder-Sälejärvi & Hillyard, 1999; Rorden & Driver, 2001). To the best of my knowledge, the influence of selective attention on auditory localization has not been examined in older adults. Because the ability to attend to cued visual targets and to ignore distracting information is preserved in older adults (Guerreiro et al., 2014; Groth & Allen, 2000), older adults may also improve in auditory localization when the sound source is precued. In other words, older adults may compensate for peripheral and central auditory changes in localizing sounds with top-down control through selective attention. Thus, to extend the literature on the influence of selective attention on auditory localization and aging, this study adopted Posner s (1980) cueing paradigm. Posner s (1980) cueing paradigm is composed of providing directional knowledge about the upcoming target. Three types of attentional cues are given: 1) Valid cues, provided on 60% of the trials, gave correct information about the upcoming target location; 2) Invalid cues, provided on 20% of the trials, gave incorrect information about the upcoming target location, and 3) neutral cues, provided on 20% of the trials, gave no information about the upcoming target location. Golob et al. (2002) also adopted Posner s cueing paradigm in an auditory localization task with younger adults. Sounds were presented from three locations (0, -90 (left) and +90 (right)). Before the sounds were presented, participants were verbally given the attentional cues. Valid cues correctly indicated the sound location (e.g., left and the sound was presented from the left), invalid cues provided incorrect information about the sound location (e.g., right when the sound was presented from the left). Neutral cues did not provide any directional information (e.g., go ). Golob et al. (2002) found that participants localized sounds after valid cues faster than after neutral and invalid cues. However, they did not report differences in localization accuracy 6

12 between the attentional cues. In another study conducted by Golob and Holmes (2011), they tasked younger adults to localize sounds presented at -90, -45, 0, +45, and +90 with a target/non-target paradigm. Ultimately, Golob and Holmes (2011) found that younger adults localized targets faster than non-targets. They also reported that the localization accuracy for targets presented at the lateral positions was higher than the non-targets at the lateral positions. As Eriksen and James (1986) suggested, prior information about the target location may have helped focus the distribution of the attentional processing resources together, allowing the localization responses to be faster and more accurate. 1.5 Rationale and Hypotheses The influence of selective attention on auditory localization in older adults has not been extensively studied. To fill this gap in knowledge, younger and older adults completed an auditory localization task modified with Posner s (1980) cueing paradigm. The auditory target was a broadband noise, presented from one of five hidden loudspeakers located directly ahead (0 ) and to the left (-28 and -90 ) and right (+28 and +90 ) of the listener s head in a nonsound attenuated laboratory. Prior to the onset of the target, attentional cues were visually presented to the participants to a) provide correct information about the upcoming target location (valid), b) provide incorrect information about the upcoming target location (invalid), or c) provide no information about the upcoming target location (neutral). Based on the reviewed literature (Freigang et al., 2014, 2015; Golob et al., 2002; Golob & Holmes, 2011), this study evaluated the following hypotheses: 1) Younger adults will localize the target more accurately and faster than older adults overall. 2) The target will be localized more accurately and faster after valid cues than after neutral and invalid cues. 3) The target presented at -90 and +90 will be localized less accurately than those at -28, 0, and

13 4) Improvements in localization accuracy and response time associated with valid cues will be proportionally greater in older adults than in younger adults. 2 Method 2.1 Participants Sixteen younger adults (M = 22.19, SD = 2.43; 5 males) and fifteen older adults (M = 68.13, SD = 3.46; 3 males) were recruited by flyers posted at the University of Toronto and Toronto Rehabilitation Institute. Prospective participants were screened over the telephone for health conditions that could impair attention, auditory localization abilities, and/or performance on the pointing response task (e.g. diagnosed hearing loss, arthritis in the hand or arm). Eligible participants were then brought into the lab and completed audiometric testing in a sound booth to ensure their pure-tone air conduction thresholds were less than or equal to 25 db (for younger adults) or 30 db (for older adults) for frequencies from 0.25 to 4 khz in both ears (procedure described in section 2.2.1). Older adults were also screened for cognitive impairment with the Montreal Cognitive Assessment (MOCA); those with a score of less than or equal to 25 (out of 30 points) were excluded. Participants were compensated $10 per hour. This study was approved by the research ethics board at Toronto Rehabilitation Institute. 2.2 Materials Audiometric Testing The audiometric test was conducted with a Grason-Stadler 61 Clinical Audiometer and Sennheiser headphones in a dimly lit sound booth. The heard/not-heard detection paradigm was used. The right ear (or the self-reported better ear) was always tested first. The test began at 1000 Hz with the sound intensity set at 40 db. If participants responded to the tone by saying yes through the headset, the intensity was lowered from 40 db to 30 db. The intensity always lowered in increments of 10 db until there was no response. When a response was given, the intensity was always increased by 5 db HL. Once three responses ( yes ) to a particular intensity were made, the intensity was recorded. After testing 1000 Hz, the lower frequencies (250, 500, and 500 Hz) were tested, and then the higher frequencies (2000, 3000, and 4000 Hz), all of which began at the sound intensity of 40 db. Once the testing of the right ear or the self-reported 8

14 better ear was finished, the other ear was tested. The audiometric test took approximately 10 minutes to complete Auditory Target The auditory target in the auditory localization task was a broadband Gaussian noise generated in Audacity. The target was presented at 60 db from one of five loudspeakers (Meyer-sound MP- 4XP) hidden behind a projector screen in the testing environment (see section 2.2.3). The center loudspeaker was located straight ahead of the participant at 0, and the lateral loudspeakers were at -90, -28 (left), and +90 and +28 (right). Participants sat 2.14 m away from the loudspeakers. See Figure 1. In the practice blocks, the target was presented at 70 db to emphasize learning the trial procedure Testing Environment The study was conducted in a laboratory located within Toronto Rehabilitation Institute s Challenging Environment Assessment Laboratory under dim lighting conditions. The acoustical properties of the laboratory were measured with a Norsonic NOR140 sound level meter, serial number The reverberation times in the laboratory were within the range deemed acceptable by ANSI standards for a teaching environment, and the average background sound level was 43 db(a) with no equipment operating (Campos et al., 2016) Visual Cues and Response On a Samsung Galaxy Tab 10.1, a schematic top-down drawing of the testing environment was shown to the participants (see Figure 2). The green circle on the schematic drawing represented the walls of the laboratory, and participants localized the target by using a tablet stylus (Adonit Jot Mini stylus) to tap on a location on the circle to represent the perceived target location. At the start of each trial, the location of the participant was represented with a red fixation cross in the centre of the circle. The valid and invalid cues resembled a green pie slice that originated at the participant s location and extended to the wall, highlighting an area of 30 surrounding one of the five loudspeakers. For neutral cued trials, there was no pie slice; instead, the fixation cross was coloured green to indicate to the participants that they will hear the target soon. 9

15 Participants also received feedback about their response. After the target location was indicated on the circle, a red arrow and the angular direction information were shown to help ensure that their response reflected their intended response. The red arrow originated from the participant s location on the schematic drawing, and pointed towards the tapped location. The angular direction information of the tapped location was shown at the bottom of the tablet screen. See Figure 2. The brightness setting was optimized by the electronic touch tablet to ensure the visual cues were consistently visible. The tablet was placed horizontally on a stand that was positioned directly in front of the participant (see Figure 1). The height of the stand was adjusted for each participant to ensure they maintained an upright head position, and that the tablet would not occlude the speaker at 0. A foam armrest was provided to reduce physical discomforts such as fatigue Auditory Localization Task The auditory localization task was completed on the electronic touch tablet. The task consisted of five blocks of 100 trials each (500 trials total). Based on the previous studies (e.g., Golob et al., 2002; Posner, 1980), each block presented 60 valid cues, 20 neutral cues, and 20 invalid cues. The target was presented at each location (-90, -28, 0, +28, +90 ) equally often. The trials within each block were randomized. There were also two practice blocks, each composed of 10 trials (6 valid trials, 2 neutral trials and 2 invalid trials). The trial procedure of the practice blocks was identical to the experimental blocks. 10

16 Figure 1. Diagram of the testing environment in aerial view. Participants sat at equidistance (2.14 m) from the five physical loudspeakers at -90, -28, 0, +28, +90. The loudspeakers were hidden from view by a 240 projection screen. 2.3 Procedure Participants first completed the audiometric test to ensure the minimum hearing criteria were met. Older participants also completed the MOCA to ensure the cognitive criteria were met. Participants who did not meet the hearing and/or cognitive criteria did not complete the study. Before the auditory localization task, participants were instructed that the target will be presented from the walls of the laboratory; therefore, the main task was to indicate the direction of the target, relative to their sitting position, on the schematic drawing. Participants were also instructed to locate the target as quickly and as accurately as they can, and to maintain their gaze towards the fixation cross on the tablet without moving their head or body. Participants completed the two practice blocks to first familiarize themselves with the trial procedure. At the beginning of each trial, a red fixation cross appeared on the center of the schematic drawing. The participant tapped the red fixation cross to continue the trial and held the stylus in 11

17 position until the target was heard. After tapping the red fixation cross, the attentional cue was presented for 250 milliseconds. The interval between the offset of the cue and the onset of the target was 600 milliseconds. The target was then played for 500 ms from one of the five loudspeakers. When the target finished playing, the fixation cross transformed into a white X to prompt the participant s response. The participant then tapped on the circumference of the circle to estimate their perceived location of the target. The maximum allowed response time window was 7 seconds. After their response, a red arrow appeared as feedback. The feedback extended from the center to the touched location on the schematic drawing for 1 second. Simultaneously, the exact angular position in degrees corresponding to the response was shown at the bottom of the tablet screen. To indicate the end of the current trial, the white X changed back into a red fixation cross. The next trial began when the participant placed the stylus back on the red fixation cross. See Figure 2 for the trial procedure. Each practice block took less than one minute to complete. Each experimental block took around 10 minutes to complete. There were mandatory breaks after every two experimental blocks. Additional breaks were offered at the end of each block. At the end of the auditory localization task, the experimenter debriefed and compensated the participants. 12

18 Figure 2. Trial procedure of the auditory localization task (A). This exemplifies a valid trial in the auditory localization task. The attentional cue was centered at -90. The red circle indicates that the target was presented at -90. Note that participants were not shown the placements of the physical loudspeakers. (B) is a screenshot of the auditory localization task during feedback. 2.4 Design A 2 x 3 x 5 mixed-factorial design was used. The independent variables included age group (younger vs. older adults), types of attentional cues (valid vs. neutral vs. invalid), and location (-90 vs. -28 vs. 0 vs. +28, vs. +90 ). Age group was a between-participant factor, whereas the types of attentional cues and location were within-participant factors. The dependent variables included localization accuracy, which was quantified as 1) absolute error (degrees), and 2) signed error (degrees), and response time (ms). 13

19 3 Results For each dependent variable (i.e., absolute error, signed error, response time), a 2 (age group) x 3 (attentional cue) x 5 (location) mixed-factorial ANOVA was conducted. Thereafter, a Bonferonni post-hoc test was conducted to examine pairwise differences for each significant main and interaction effects. No trials were excluded from the analyses. 3.1 Absolute Error Absolute error, defined as the magnitude of unsigned error, was calculated by obtaining the absolute angular difference between the perceived target location and the actual target location. The closer the value is to 0, the closer the perceived target location was to the actual target location. For example, if the target was at -90, and the participant responded -85, the absolute error of that trial would be 5. This would indicate the response was off by 5 (smaller magnitude of error), whereas if they responded +15, the response would be off by 75 (larger magnitude of error). The ANOVA showed a significant main effect of attentional cue, F(2, 58) = 61.78, p <.01, η 2 p =.68. The post-hoc test indicated that the targets preceded by valid cues had smaller mean absolute error than for targets preceded by neutral (p <.01) and invalid cues (p <.01; Figure 3). There was also a significant main effect of location, F(4, 116) = 45.16, p <.01, η 2 p =.61. The post-hoc test indicated that the mean absolute error of targets at -28 and +28 were higher than the targets at -90, +90, and 0 (p <.01 for all comparisons; see Figure 4). 14

20 Absolute Error (Degrees) Absolute Error (Degrees) Valid Neutral Invalid Attentional Cue Type Figure 3. Mean absolute error (degrees) between the three different attentional cue types collapsed across location and age groups. Error bars represent ±2 SE Azimuth of Sound Location (Degrees) Figure 4. Mean absolute error (degrees) between the five locations collapsed across age groups and the attentional cue types. Error bars represent ±2 SE. 15

21 Absolute Error (Degrees) There was a significant interaction effect between attentional cue and location, F(8, 232) = 10.05, p <.01, η 2 p =.26. The post-hoc test indicated that the valid cues had the lower mean absolute error compared to neutral and invalid cues at all locations (p <.01) except at +90, where the mean absolute error of valid cues was not significantly different from neutral cues (p >.05). The post-hoc test also indicated that the mean absolute error of neutral cues was not statistically different than invalid cues for targets presented at -90 (p >.05) and +28 (p >.05). See Figure Valid Neutral Invalid Azimuth of Sound Location (Degrees) Figure 5. Mean absolute error (degrees) between the five locations clustered by the three different attentional cue types. Error bars represent ±2 SE. There were no other significant effects (p >.05), which suggested that younger and older adults performed similarly in absolute error across the different attentional cue and location trials. 3.2 Signed Error Signed error was calculated by obtaining the angular difference between the perceived target location and the actual target location. Thus, the directional bias of the error was indicated by a positive or negative value. A positive value indicated a rightward bias of the error relative to the 16

22 Signed Error (Degrees) physical target location, and a negative value indicated a leftward bias. For example, if the target was at -90, and the perceived target was at -80, the signed error would be +10. This value would indicate that the perceived response was off by 10, and that it was localized towards the right side of the actual target location. The closer the value is to 0, the closer the perceived target location was made from its actual target location. The ANOVA revealed a significant main effect of attentional cue, F(2, 58) = 4.97, p <.01, η 2 p =.15. The post-hoc test indicated that the targets preceded by valid cues had less leftward bias compared to invalid cues (p <.01). No other pairwise comparisons between the attentional cues were significant (p >.05). This indicated that the leftward biases for valid cues were comparable to neutral cues, and that the neutral cues were comparable to invalid cues (Figure 6) Valid Neutral Invalid Attentional Cue Type Figure 6. Mean signed error (degrees) between the three different attentional cue types collapsed across location and age groups. Error bars represent ±2 SE. There was also a significant main effect of location, F(4, 116) = 69.16, p <.01, η p 2 =.71. The post-hoc test showed that all of the locations had different mean signed error from each other (p <.01) except for 0 vs. +90 (p >.05; Figure 7). 17

23 Signed Error (Degrees) Azimuth of Sound Location (Degrees) Figure 7. Mean signed error (degrees) between the five locations collapsed across age groups and the attentional cue types. The error bars represent ±2 SE. There was a significant interaction between attentional cue and location, F(8, 232) = 25.98, p <.01, η p 2 =.48. The post-hoc test showed that the targets preceded by valid cues had smaller mean signed error compared to neutral and invalid cues at all locations (p <.05) except for 0 and +90 (p >.05). At 0 and +90, the leftward biases associated with valid and neutral cues were comparable. The post-hoc test also showed that at -28, +28, and +90, the mean signed error associated with neutral and invalid cues were comparable. See Figure 8. No other pairwise comparisons were significant (p <.05), which indicated that older adults had mean signed error comparable to younger adults across the different attentional cue and location trials. 18

24 Signed Error (Degrees) Valid Neutral Invalid Azimuth of Sound Locations (Degrees) Figure 8. Mean signed error (degrees) between the five locations clustered by the three different attentional cue types. Error bars represent ±2 SE. 3.3 Response Time Response time (ms) was the time after the target was presented to the moment the participant responded on the schematic drawing by tapping the tablet with the stylus. The lower the response time, the faster the target was localized. The ANOVA showed a significant main effect of attentional cue, F(2, 58) = 79.02, p <.01, η 2 p =.73. The post-hoc test indicated that the responses after valid cues were faster than after neutral (p <.01) and invalid cues (p <.01). However, the response times for neutral and invalid cues were not significantly different from each other, p >.05 (Figure 9). 19

25 Response Time (ms) Valid Neutral Invalid Attentional Cue Type Figure 9. Mean response time (ms) between the three different attentional cue types collapsed across location and age groups. Error bars represent ±2 SE. There was a significant main effect of location, F(2, 58) = 79.02, p <.01, η p 2 =.73. The post-hoc test indicated that the response times for targets at the right-side locations (+28 and +90 ) were faster than the targets at directly ahead (0 ) and the left-side locations (-90 and -28 ), p <.01 for all comparisons. Meanwhile, the response times for the right-side target locations did not differ from each other, p >.05. The response times for the targets presented on the left-side and directly ahead also did not differ statistically from each other, p >.05. See Figure

26 Response Time (ms) Azimuth of Sound Location (Degrees) Figure 10. Mean response time (ms) between the five locations collapsed across age groups and the attentional cue types. Error bars represent ±2 SE. Lastly, there were significant interaction effects with the between-subject factor, age group. The interaction between age group and attentional cue was small but significant, F(2, 58) = 3.93, p =.03, η p 2 =.12. The post-hoc test indicated that for older adults, the response times after valid cues were faster than invalid cues, and that invalid cues were faster than neutral cues, p <.01 for all comparisons. In younger adults, response times after valid cues were faster than neutral and invalid trials, p <.01; however, response times between neutral and invalid cues did not differ from each other, p >.05 (Figure 11). 21

27 Response Time (ms) Younger Adults Older Adults Valid Neutral Invalid Attentional Cue Type Figure 11. Mean response time (ms) between the three different attentional cue types clustered by age groups. Error bars represent ±2 SE. There was also a small, but significant interaction between age group and location, F(4, 116) = 2.93, p =.02, η p 2 =.09. The post-hoc test showed that younger adults responded to the targets on the left-side locations slower than targets on the right-side locations and directly ahead, p <.01. Older adults responded slower to the targets on the left-side locations and directly ahead than the targets on the right-side locations, p <.01. See Figure

28 Response Time (ms) Younger Adults Older Adults Azimuth of Sound Location (Degrees) Figure 12. Mean response time (ms) between the five locations clustered by age groups. Error bars represent ±2 SE. 4 Discussion Literature has shown that older adults typically localize sounds less accurately than younger adults due to age-related changes in the peripheral and central auditory system (e.g., Freigang et al., 2014). Thus, this study investigated whether selective attention may compensate for the deficits in auditory localization in older adults (e.g., Golob et al., 2002; Golob & Holmes, 2011). In a typical non-sound attenuated laboratory, the auditory target, a broadband noise, was presented at one of five hidden locations in the horizontal plane: -90, -28, 0, +28, and +90. Selective attention was manipulated by visually cueing the target location, and that was either 1) valid, in that attention was directed towards the upcoming target location, 2) invalid, in that attention was directed towards another location, or 3) neutral, in that no directional information was provided. Localization performance was then assessed by measuring 1) absolute error 23

29 (degrees) and 2) signed error (degrees), and 3) response time (ms). The next sections will discuss localization accuracy and response time separately, and then considered together at the end. 4.1 Localization Accuracy Contrary to my initial hypothesis, younger adults were not more accurate at localizing the broadband noise than were older adults overall. This was unexpected because the age differences in the previous studies were quite large (i.e., 15% difference in accuracy between younger and older adults in Abel et al. s (2000) study, and 21% in Freigang et al. s (2014) study). This suggests that broadband noise is easy to localize accurately for both younger and older adults, and it might be easy because broadband noise contains more sound cues (ITDs and ILDs; Middlebrooks & Green, 1991). In fact, previous studies found that the overall localization accuracy of broadband noise was near ceiling unlike pure-tone noise, which was localized less accurately (Abel et al., 2000; Dobreva et al., 2000). If this study compared broadband noise with pure-tone noise, which contains less sound cues, age differences in localization accuracy may be apparent. This study also did not find age differences in localization accuracy across the different types of attentional cues. Broadband noise preceded by valid cues had lower localization errors and smaller biases compared to neutral cues and invalid cues in both younger and older adults. This supported the hypothesis that the broadband noise was localized more accurately with valid cues; however, this did not support the hypothesis that the valid cues improved localization accuracy proportionally more in older adults than in younger adults. As proposed previously, the broadband noise may be easy to localize for both younger and older adults, therefore further information about its location may not significantly improve accuracy. These findings compliment the literature on selective attention and aging (e.g., Groth & Allen, 2000), though. Because older and younger adults had similar localization errors and biases across the types of attentional cues, this suggests that older adults were as capable as younger adults in employing selective attention to improve performance (e.g., Geuerreiro et al., 2014). Specifically, older adults can distribute attentional processing resources based on prior knowledge of the sound and respond more accurately (e.g., Groth & Allen, 2000), similar to younger adults (Golob et al., 2002; Golob & Holmes, 2011). Based on the zoom-lens analogy (Eriksen & St. James, 24

30 1986), the valid attentional cue may have allowed participants to direct attentional processing resources towards the attended location more efficiently. Consequently, localization responses were more accurate than when the attentional processing resources were focused at the wrong location or across the entire field (e.g., from -90 to +90 ). The current study also did not find age differences in localization accuracy across the five locations, indicating that younger and older adults made similar localization errors and biases at -90, -28, 0, +28, and +90. Particularly, this study found that localizing the broadband noise presented at -28 and +28 had greater errors and leftward and rightward biases, respectively (see Figure 7). This did not support the hypothesis that the broadband noise at -90 and +90 would be localized the least accurately, and is inconsistent with the previous literature (e.g., Freigang et al., 2014; 2015). Specifically, previous studies showed that localization accuracy declined as sounds were presented more laterally (Abel et al., 2000; Dobreva et al., 2011; Freigang et al., 2014). The answer to why the broadband noise presented at -90 and +90 were easier to localize than at -28 and +28 is not clear. One possibility is that the sound cues of the broadband noise at -90 and +90 were more clearly attenuated at one ear than the other ear. For instance, if the sound pressure level (ILD) was stronger in the left ear than in the right ear, there may be greater certainty that the sound was located on the left side. At -28 and +28, the differences of the sound pressure level between the left and right ear may be smaller; thus, the perceived location may be harder to determine. However, this does not completely explain the discrepancy from the literature. It is possible that the reverberation in the testing environment also influenced the perceived differences of the sound pressure level and arrival time. Previous studies were conducted in anechoic and semi-reverberant environments (e.g., Freigang et al., 2014); thus, the perceived sound cues were not influenced by acoustical factors such as reverberation. In this study, the reverberation times may have enhanced the sound cues at -90 and +90, thus improving localization accuracy at these locations, but reduced the sound cues at -28 and +28, therefore lowering localization accuracy at these locations. However, this study cannot ascertain this occurrence or specify its influence due to limitations in the current design (e.g., changes in the 25

31 sound pressure levels of the broadband noise were not measured). Future directions may include replicating this study in an acoustically-controlled environment (i.e., sound booth) to ascertain the differences between the lateral sound locations. 4.2 Response Time As predicted, this study showed that younger adults localized the broadband noise faster than older adults overall. This suggests that younger adults can detect and identify the location of the broadband noise on the schematic drawing faster than older adults. But because younger and older adults had comparable hearing thresholds (which may associate with detecting the sound cues) and similar localization accuracy (which may associate with integrating the sound cues to identify the location), differences in motor reflexes and/or familiarity with the electronic devices may better explain this finding. For instance, younger adults may have responded faster because they have better motor control of their hand/arm. Younger and older adults also had different patterns of response times with the attentional cues. While both groups localized broadband noise faster after valid cues, older adults responded slower after neutral cues than after invalid cues, and younger adults responded similarly between neutral and invalid cues (see Figure 11). Older adults may have found that any directional information is helpful, regardless of whether it was correct or incorrect, compared to not receiving directional information at all when it comes to responding quickly. These findings compliment the attention literature (e.g., Groth & Allen, 2000), such that responses after valid cues are known to be faster than responses after invalid cues and neutral cues (e.g., Posner, 1987; Golob et al., 2002; Madden et al., 1994; Spence & Driver, 1997), and extend the current literature on attention to auditory localization in older adults. However, it is unclear why older adults responded slower after neutral cues than after invalid cues, as studies have shown that responses after invalid cues are typically slower than after neutral cues (e.g., Golob et al., 2002; Groth and Allen, 2000). One possibility, based on the zoom-lens analogy (Eriksen and St. James, 1986), is that the attentional processing resources were spread too sparsely across the testing environment in neutral-cued trials. When the attentional cue was invalid, the processing resources were at least focused together, which may have allowed the older adults to shift to the new attended location more efficiently. Meanwhile, 26

32 whether the processing resources were focused together or spread apart may not have mattered to younger adults, who may have compensated for this with better motor and/or cognitive processes (i.e., quickly re-positioning their hand to tap the correct location and/or attending to the more relevant location). Finally, this study found that younger and older adults might have variable response times between the locations, which were not expected. In fact, previous studies on auditory localization have not reported age differences in localizing sounds in terms of response time (Abel et al., 2000; Dobreva et al., 2011; Freigang et al., 2014). In this study, both groups localized the broadband noise on the right side (+28 and +90 ) faster than on the left side (-28 and -90 ), but interestingly, older adults also responded slower when the broadband noise was presented directly ahead (0 ; see Figure 12). Since attentional cues did not influence response times between the locations, it is unlikely that the size of the attended field or the distribution of the processing resources played any role in this finding. This may instead indicate the right side of the tablet was easier to respond quickly than on the left side of the tablet. For older adults, quickly pinpointing a location close to 0 on the tablet may also be difficult. 4.3 Summary of the Results Overall, the findings suggest that older adults are able to modulate attentional processing resources to improve auditory localization performances, similar to younger adults. Specifically, when older adults direct their attention towards the upcoming target location, they may localize the target faster and with less errors and less biases that are comparable to younger adults. However, this study found that older adults responded slower to targets that were preceded by neutral cues, suggesting that some directional information may be better than no directional information. Some of the discrepancy from the reviewed literature may be due to using broadband noise and not accounting for acoustical factors in the environment and other agerelated sensory and cognitive changes. A follow-up study would be to include high- and lowfrequency noise, and replicate the design in an anechoic environment. This will expand on the findings on selective attention in auditory localization and aging, and address potential acoustical confounds in the environment. 27